We examined the impact of chronic prostatitis on the diagnostic performance of multiparametric magnetic resonance imaging (mpMRI). In this retrospective study, 63 men underwent 3T mpMRI followed by MRI/ultrasound fusion biopsy to exclude/confirm clinically significant prostate cancer (csPCa). A total of 93 lesions were included for evaluation. Images were assessed by two radiologists. Prostatitis was graded visually on T2-weighted and contrast-enhanced sequences. The correlation of prostatitis features with the assigned Prostate Imaging Reporting and Data System (PI-RADS) and the presence of csPCa were assessed, and the clinical and functional imaging parameters for differentiating between prostatitis and significant tumors were examined. Histopathological analysis was used as the reference standard. The rate of PI-RADS 3 scores tended to be higher in the presence of radiologically severe prostatitis compared with no/discrete prostatitis (n = 52 vs. n = 9; p = 0.225). In severe prostatitis, csPCa was determined in only 7.7% (4/52) of PI-RADS 3 lesions. In severe chronic prostatitis, a binary prostatitis suffix (e.g., PI-RADS 3 i+ versus i-) within the radiological report may help assess the limitations of mpMRI interpretability because of severe prostatitis and avoid unnecessary biopsies. Mean apparent diffusion coefficient (ADCmean) was the best marker (cutoff 0.93 × 10-3 mm2/s) to differentiate between csPCa/non csPCa in severe prostatitis.
Diagnostics (Basel, Switzerland). 2021 Mar 30*** epublish ***
Sascha Merat, Theresa Blümlein, Markus Klarhöfer, Dominik Nickel, Gad Singer, Frank G Zöllner, Stefan O Schoenberg, Rahel A Kubik-Huch, Daniel Hausmann, Lukas Hefermehl
Department of Radiology, Kantonsspital Baden, 5404 Baden, Switzerland., Eidgenössische Technische Hochschule (ETH) Zürich, 8092 Zurich, Switzerland., Siemens Healthcare AG, 8047 Zürich, Switzerland., MR Applications Predevelopment, Siemens Healthcare GmbH, 91052 Erlangen, Germany., Department of Pathology, Kantonsspital Baden, 5404 Baden, Switzerland., Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany., Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany., Department of Urology, Kantonsspital Baden, 5404 Baden, Switzerland.